Asset Risk Senior Risk Modeller

Motability Operations
London
1 month ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Engineer

Data Analytics & Data Science Lead

Master Data Analyst

Data Engineer (Asset Management)

Data Engineer (Asset Management)

This job is brought to you by Jobs/Redefined, the UK's leading over-50s age inclusive jobs board.

About The Role

The Asset Risk Senior Risk Modeller role sits in the Asset Risk Function, which has the responsibility for forecasting Motability Operation's key financial risks, including Residual Value and SMR, Insurance Lease Pricing, Economic Capital, as well as producing the customer pricing. This role sits in the Asset Risk Modelling Team, operating in a matrix way of working, responsible for delivering a strong model risk management framework, and ensuring all forecast models are robustly implemented, operated, enhanced and developed in conjunction with joint ownership for the outcomes and outputs with business SME's.

Reporting into the Asset Risk Modelling Manager, the role has the following key responsibilities:

  • You will proactively support and inform the delivery of the Asset Risk strategy in alignment with the needs of the wider business strategy.
  • You will work with the Modelling Manager to oversee the operational delivery of the model risk management framework in Asset Risk, ensuring model health, reporting, processing, auditing and reporting requirements are met and provide steer and challenge to ensure improvements are approved and delivered.
  • You will take the lead and proactively engage with the critical thinking and operational activity needed for the accurate and timely delivery of the critical BAU requirements for all key models associated with residual value forecasting, maintenance spend, insurance, customer pricing, and economic capital.
  • You will maintain a deep understanding of, and be responsible for the challenging of, the model components - design principles, use of data, assumptions, applied statistical and modelling techniques - for the BAU models, helping to create and deliver the effective communication required to bridge the gap between the models and Asset Risk deliverables.
  • You will take the lead and proactively engage with the critical thinking and activity required to deliver the strategic projects from the Modelling team, ensuring all deliverables and outcomes are jointly owned with business SME's.
  • You will work with the Modelling Lead to ensure the Modelling Team are as engaged with explaining and owning the outputs and outcomes as they are with operating and developing our models, and with the equivalent engagement from non-modelling teams.
  • You will proactively challenge the way we work, and feed into the Asset Risk Strategy roadmap, and support in ad hoc queries where possible.
  • You will form collaborative relationships to ensure the Model Team deliverables (BAU and strategic projects) are effectively managed and delivered in line with a matrix way of working approach across the Asset Risk Operational Teams and fellow Asset Risk output owners.
  • You will play a pivotal role in ensuring the AR Operational Teams (Programme, Product, Modelling and Data) work closely with each other to support on cross over areas (e.g. tools) and reduce the opportunity for knowledge gaps.
  • You will be an effective coach and mentor for the wider Modelling Team, working with the Modelling Manager to ensure the team and individuals have the right skills and development paths to meet the needs of the business.
  • You will be an advocate for Asset Risk, and work with colleagues around the business to promote best practices and skills & knowledge sharing.
  • You will develop collaborative and enduring relationships with the Asset Risk and wider business leadership teams, relevant stakeholders, and be an advocate for Asset Risk and our ways of working.
  • You will proactively work with the Modelling Lead to engage with relevant 3rd parties (industry bodies, commentators and experts) to ensure Asset Risk activities are appropriately aligned with external best practice.

About You

  • Planning: Ability to coordinate multiple stakeholders, colleagues and deadlines.
  • Modelling: Ability to understand, operate, and explain complex models.
  • Accuracy & attention to detail: Ensuring accuracy in models and forecasts.
  • Problem solving skills: Ability to develop solutions for complex financial problems.
  • Communication skills: Can explain technical concepts to non-technical stakeholders.
  • Commercial awareness: Can understand the business environment, market trends, and the financial impact of decisions to align models with the organisation's strategic goals.

Minimum Criteria

You'll need all of these:

  • A degree (Bachelor's or Masters) in Statistics, Mathematics, Economics, Data Science, or a related field.
  • Experience in forecasting, data analysis, or a related field.
  • Experience of delivering complex model updates (operational and development) with the effective communication of model outcomes.
  • Proven experience with statistical software (e.g., R, Python, SAS) and forecasting tools.
  • Experience managing complex projects and coaching analysts.

Desirable Criteria

  • Experience in the specific industry relevant to the forecasting role (e.g., finance, retail, manufacturing) is highly valuable.
  • Experience with advanced analytical techniques, including machine learning and predictive modelling.

About The Company

Motability Operations is a unique organisation, virtually one of a kind. We combine a strong sense of purpose with a real commercial edge to ensure we provide the best possible worry-free mobility solutions to over 815,000 customers and their families across the UK. Customers exchange their higher rate mobility allowance to lease a range of affordable vehicles (cars, wheelchair accessible vehicles, scooters, and powered wheelchairs) with insurance, maintenance and breakdown assistance included. We are the largest car fleet operator in the UK (purchasing around 10% of all the new cars sold in the UK) and work with a network of around 5,000 car dealers and all the major manufacturers. We pride ourselves on delivering outstanding customer service, achieving an independently verified customer satisfaction rating of 9.8 out of 10.

Our values are at the heart of everything we do. They represent ambition, and we look for our people to live and breathe them every day:

  • We find solutions.
  • We drive change.
  • We care.

We operate hybrid working across the organisation where we split our time between working on-site at our offices, and at home, remotely within the UK. We believe hybrid working achieves a good work/life balance for our colleagues, allowing us to connect with each other, collaborate on important work, and perform together to deliver for our customers. It allows us to have the flexibility to work remotely up to 2-days per week whilst also using the great office spaces we have available.

As a Motability Operations team member, the benefits you can expect are:

  • Competitive reward package including an annual discretionary bonus.
  • 15% non-contributory pension (9% non-contributory pension during probation period).
  • 28 days annual leave with option to purchase and sell days.
  • Free fresh fruit and snacks in the office.
  • 1 day for volunteering.
  • Funded Private Medical Insurance cover.
  • Electric/Hybrid Car Salary Sacrifice Scheme and Cycle to Work Scheme.
  • Life assurance at 4 times your basic salary to give you a peace of mind that your loved ones will receive some financial help.
  • Funded health screening for over 50s.
  • Voluntary benefits: charitable giving, critical illness insurance, dental insurance, health and cancer screenings for you and your partner, discounted gym memberships and season ticket loans.
  • Employee Discount Scheme with an app to save on the go.
  • Free access to healthcare apps such as Peppy, Unmind, Aviva Digital GP and volunteering app on Hand for all employees.
  • Generous family leave policies.

At Motability Operations, we believe in building a diverse workforce, where our people are empowered to attend work as their true selves, and we encourage people from all backgrounds to apply. We want to sustain a culture that nurtures, where employees are free to flourish and where they're rewarded equally, regardless of race, nationality or ethnic origin, sexual orientation, age, disability, or gender.

We pride ourselves on being an inclusive employer and as such, all our offices provide first rate disability access. With our hybrid working environment, we do our best to accommodate part-time and flexible working requests where possible, building on our culture of trust, empowerment, and flexibility.

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

Machine Learning Jobs in the Public Sector: Opportunities Across GDS, NHS, MOD, and More

Machine learning (ML) has rapidly moved from academic research labs to the heart of industrial and governmental operations. Its ability to uncover patterns, predict outcomes, and automate complex tasks has revolutionised industries ranging from finance to retail. Now, the public sector—encompassing government departments, healthcare systems, and defence agencies—has become an increasingly fertile ground for machine learning jobs. Why? Because government bodies oversee vast datasets, manage critical services for millions of citizens, and must operate efficiently under tight resource constraints. From using ML algorithms to improve patient outcomes in the NHS, to enhancing cybersecurity within the Ministry of Defence (MOD), there’s a growing demand for skilled ML professionals in UK public sector roles. If you’re passionate about harnessing data-driven insights to solve large-scale problems and contribute to societal well-being, machine learning jobs in the public sector offer an unparalleled blend of challenge and impact. In this article, we’ll explore the key reasons behind the public sector’s investment in ML, highlight the leading organisations, outline common job roles, and provide practical guidance on securing a machine learning position that helps shape the future of government services.

Contract vs Permanent Machine Learning Jobs: Which Pays Better in 2025?

Machine learning (ML) has swiftly become one of the most transformative forces in the UK technology landscape. From conversational AI and autonomous vehicles to fraud detection and personalised recommendations, ML algorithms are reshaping how organisations operate and how consumers experience products and services. In response, job opportunities in machine learning—including roles in data science, MLOps, natural language processing (NLP), computer vision, and more—have risen dramatically. Yet, as the demand for ML expertise booms, professionals face a pivotal choice about how they want to work. Some choose day‑rate contracting, leveraging short-term projects for potentially higher immediate pay. Others embrace fixed-term contract (FTC) roles for mid-range stability, or permanent positions for comprehensive benefits and a well-defined career path. In this article, we will explore these different employment models, highlighting the pros and cons of each, offering sample take‑home pay scenarios, and providing insights into which path might pay better in 2025. Whether you’re a new graduate with a machine learning degree or an experienced practitioner pivoting into an ML-heavy role, understanding these options is key to making informed career decisions.